When Shared Autonomous Electric Vehicles Meet Microgrids: Citywide Energy-Mobility Orchestration

2021 ◽  
Author(s):  
Wei Qi ◽  
Mengyi Sha ◽  
Shanling Li
Keyword(s):  
New York ◽  
Electric Vehicles ◽  
Problem Definition ◽  
Service Systems ◽  
Fleet Size ◽  
Mobility Service ◽  
Trade Offs ◽  
Self Sufficiency ◽  
Managerial Implications ◽  
Autonomous Electric Vehicles

Problem definition: We develop a crossdisciplinary analytics framework to understand citywide mobility-energy synergy. In particular, we investigate the potential of shared autonomous electric vehicles (SAEVs) for improving the self-sufficiency and resilience of solar-powered urban microgrids. Academic/practical relevance: Our work is motivated by the ever-increasing interconnection of energy and mobility service systems at the urban scale. We propose models and analytics to characterize the dynamics of the SAEV-microgrid service systems, which were largely overlooked by the literature on service operations and vehicle-grid integration (VGI) analysis. Methodology: We develop a space-time-energy network representation of SAEVs. Then, we formulate linear program models to incorporate an array of major operational decisions interconnecting the mobility and energy systems. To preventatively ensure microgrid resilience, we also propose an “N − 1” resilience-constrained fleet dispatch problem to cope with microgrid outages. Results: Combining eight data sources of New York City, our results show that 80,000 SAEVs in place of the current ride-sharing mobility assets can improve the microgrid self-sufficiency by 1.45% (benchmarked against the case without grid support) mainly via the spatial transfer of electricity, which complements conventional VGI. Scaling up the SAEV fleet size to 500,000 increases the microgrid self-sufficiency by 8.85% mainly through temporal energy transfer, which substitutes conventional VGI. We also quantify the potential and trade-offs of SAEVs for peak electricity import reduction and ramping mitigation. In addition, microgrid resilience can be enhanced by SAEVs, but the actual resilience level varies by microgrids and by the hour when grid contingency occurs. The SAEV fleet operator can further maintain the resilience of pivotal microgrid areas at their maximum achievable level with no more than a 1% increase in the fleet repositioning trip length. Managerial implications: Our models and findings demonstrate the potential in deepening the integration of urban mobility and energy service systems toward a smart-city future.

scholarly journals An Integrated Optimisation-Simulation Framework for Scalable Smart Charging and Relocation of Shared Autonomous Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3633
Author(s):  
Riccardo Iacobucci ◽  
Raffaele Bruno ◽  
Jan-Dirk Schmöcker
Keyword(s):  
New York ◽  
New York City ◽  
Electric Vehicles ◽  
Simulation Framework ◽  
Electricity Prices ◽  
Electricity Storage ◽  
Smart Charging ◽  
Charging Strategy ◽  
Independent Optimisation ◽  
Autonomous Electric Vehicles

Ride-hailing with autonomous electric vehicles and shared autonomous electric vehicle (SAEV) systems are expected to become widely used within this decade. These electrified vehicles can be key enablers of the shift to intermittent renewable energy by providing electricity storage to the grid and offering demand flexibility. In order to accomplish this goal, practical smart charging strategies for fleets of SAEVs must be developed. In this work, we present a scalable, flexible, and practical approach to optimise the operation of SAEVs including smart charging based on dynamic electricity prices. Our approach integrates independent optimisation modules with a simulation model to overcome the complexity and scalability limitations of previous works. We tested our solution on real transport and electricity data over four weeks using a publicly available dataset of taxi trips from New York City. Our approach can significantly lower charging costs and carbon emissions when compared to an uncoordinated charging strategy, and can lead to beneficial synergies for fleet operators, passengers, and the power grid.

Payment Models to Coordinate Healthcare Providers with Partial Attribution of Outcome Costs

2021 ◽  
Author(s):  
Sampath Rajagopalan ◽  
Chunyang Tong
Keyword(s):  
General Practitioner ◽  
Healthcare System ◽  
Healthcare Providers ◽  
Treatment Decisions ◽  
Problem Definition ◽  
Bundled Payment ◽  
Trade Offs ◽  
Payment Schemes ◽  
Managerial Implications ◽  
Specialist Treatment

Problem definition: In many healthcare systems, general practitioners refer patients to specialists, who make treatment decisions under limited capacity. We evaluate the effectiveness of different payment schemes, both traditional ones, where the payer contracts separately with the providers, and bundled schemes, where the providers share a single bundled payment. A key feature considered is a performance-based payment component to coordinate the decisions of the general practitioner and specialist by a single payer. The providers are partially responsible for the patient outcomes and costs stemming from their treatment decisions. Academic/practical relevance: We propose and analyze a model to address how referral and specialist treatment decisions in healthcare impact each other and how payment schemes impact the coordination of care between the general practitioner and specialist. Our work is valuable to policymakers in understanding the trade-offs between using bundled and unbundled payment schemes in a referral-based healthcare system. Methodology: The underlying research method is the analysis of optimization models (with congestion effects embedded) to explore the effects of different payment schemes on different entities and various operational performance measures in a healthcare system. Results: A bundled scheme has higher referral rates, lower time spent with the patient by the specialist, higher specialist utilization relative to an unbundled system in most scenarios, and higher system costs. Our conclusions are robust to various model changes. Managerial implications: Our work provides specific managerial insights into the relative performance of bundled and unbundled payment systems on operational metrics in a referral-based healthcare system. It also sheds light on how the level of attributability of service outcomes to providers interacts with payment schemes to influence referral and specialist treatment decisions and impact various quality and cost metrics.

A Decision Support System for On-Demand Goods Delivery Using Shared Autonomous Electric Vehicles

2019 ◽  
Vol 11 (2) ◽  
pp. 72-88
Author(s):  
Amel Jaoua ◽  
Marouen Ben Ammar ◽  
Anjali Awasthi
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Electric Vehicles ◽  
Support System ◽  
Urban Areas ◽  
Strategic Decision ◽  
Fleet Size ◽  
Fleet Sizing ◽  
On Demand ◽  
Autonomous Electric Vehicles

This article presents a strategic decision support system (DSS) for on-demand delivery companies in urban areas. This DSS is designed and developed for the promising new concept of goods delivery based on a fleet of Shared Autonomous Electric Vehicles (SAEVs). A simulation-based optimization model is proposed to solve the fleet sizing and composition problems. The efficiency of the developed strategic DSS in determining best fleet size and composition under different scenarios is demonstrated. This article provides managerial insights to help goods delivery companies, who intend to use SAEVs, in determining the type and number of vehicles to acquire.

scholarly journals Inducing Compliance with Postmarket Studies for Drugs Under FDA’s Accelerated Approval Pathway

2020 ◽  
Author(s):  
Liang (Leon) Xu ◽  
Hui Zhao ◽  
Nicholas C. Petruzzi
Keyword(s):  
Public Health ◽  
Success Probability ◽  
Problem Definition ◽  
Public Access ◽  
Cost Information ◽  
Trade Offs ◽  
Clinical Benefits ◽  
Managerial Implications ◽  
Accelerated Approval ◽  
Level Of Effort

Problem definition: In 1992, the Food and Drug Administration (FDA) instituted the accelerated approval pathway (AP) to allow promising drugs to enter the market based on limited evidence of efficacy, thereby permitting manufacturers to verify true clinical benefits through postmarket studies. However, most postmarket studies have not been completed as promised. We address this noncompliance problem. Academic/practical relevance: The prevalence of this noncompliance problem poses considerable public health risk, thus compromising the original purpose of a well-intentioned AP initiative. We provide an internally consistent and implementable solution to the problem through a comprehensive analysis of the myriad complicating factors and trade-offs facing the FDA. Methodology: We adopt a Stackelberg framework in which the regulator, which cannot observe the manufacturer’s private cost information or level of effort, leads by imposing a postmarket study deadline. The profit-maximizing manufacturer then follows by establishing its level of effort to invest in its postmarket study. In establishing its deadline, the regulator optimizes the trade-off between providing public access to potentially effective drugs and mitigating public health risks from ineffective drugs. Results: We develop a deadline-dependent user fee menu as a screening mechanism that establishes an incentive for manufacturer compliance. We show that its effectiveness in inducing compliance depends fundamentally on the enforceability of sanction, a drug-specific measure that indicates how difficult it is to withdraw an unproven drug from the market, and the drug’s success probability: The higher either is, the higher is the probability that the mechanism induces compliance. Managerial implications: We synthesize and distill the salient trade-offs and nuances facing the FDA’s noncompliance problem and provide an implementable solution. We quantify the value of the solution as a function of a drug’s success probability and enforceability. From a public policy perspective, we provide guidance for the FDA to increase the viability and effectiveness of AP.

Queues with Redundancy: Is Waiting in Multiple Lines Fair?

2021 ◽  
Author(s):  
Leela Nageswaran ◽  
Alan Scheller-Wolf
Keyword(s):  
Organ Transplantation ◽  
Numerical Study ◽  
Arrival Rate ◽  
Problem Definition ◽  
Service Systems ◽  
Equitable Access ◽  
Policy Makers ◽  
Managerial Implications ◽  
Shortest Queue ◽  
To Receive

Problem definition: We study service systems where some (so-called “redundant”) customers join multiple queues simultaneously, enabling them to receive service in any one of the queues, while other customers join a single queue. Academic/practical relevance: The improvement in overall system performance due to redundant customers has been established in prior work. We address the question of fairness—whether the benefit experienced by redundant customers adversely affects others who can only join a single line. This question is particularly relevant to organ transplantation, as critics have contended that multiple listing provides unfair access to organs for patients based on wealth. Methodology: We analyze two queues serving two classes of customers; the redundant class joins both queues, whereas the nonredundant class joins a single queue randomly. We compare this system against a benchmark wherein the redundant class resorts to joining the shortest queue (JSQ) if multiple queue joining were not allowed, capturing the most likely case if multilisting was prohibited: Affluent patients could still afford to list in the region with the shorter wait list. Results: We prove that when the arrival rate of nonredundant customers is balanced across both queues, they actually benefit under redundancy of the other class—that is, redundancy is fair. We also establish that redundancy may be unfair under some circumstances: Nonredundant customers are worse off if their arrival rate is strongly skewed toward one of the queues. We illustrate how these findings apply in the organ-transplantation setting through a numerical study using publicly available data. Managerial implications: Our analysis helps identify when, and by how much, multiple listing may be unfair and, as such, could be a useful tool for policy makers who may be concerned with trying to ensure equitable access to resources, such as organs, across patients with differing wealth levels.

Ride-Hailing Platforms: Competition and Autonomous Vehicles

2022 ◽  
Author(s):  
Auyon Siddiq ◽  
Terry A. Taylor
Keyword(s):  
Social Welfare ◽  
Autonomous Vehicles ◽  
Sufficient Conditions ◽  
Structural Effect ◽  
Problem Definition ◽  
Theoretic Model ◽  
Fleet Size ◽  
Managerial Implications ◽  
Public Policy Decisions ◽  
Necessary And Sufficient

Problem definition: Ride-hailing platforms, which are currently struggling with profitability, view autonomous vehicles (AVs) as important to their long-term profitability and prospects. Are competing platforms helped or harmed by platforms’ obtaining access to AVs? Are the humans who participate on the platforms—driver-workers and rider-consumers (hereafter, agents)—collectively helped or harmed by the platforms’ access to AVs? How do the conditions under which access to AVs reduces platform profits, agent welfare, and social welfare depend on the AV ownership structure (i.e., whether platforms or individuals own AVs)? Academic/practical relevance: AVs have the potential to transform the economics of ride-hailing, with welfare consequences for platforms, agents, and society. Methodology: We employ a game-theoretic model that captures platforms’ price, wage, and AV fleet size decisions. Results: We characterize necessary and sufficient conditions under which platforms’ access to AVs reduces platform profit, agent welfare, and social welfare. The structural effect of access to AVs on agent welfare is robust regardless of AV ownership; agent welfare decreases if and only if the AV cost is high. In contrast, the structural effect of access to AVs on platform profit depends on who owns AVs. The necessary and sufficient condition under which access to AVs decreases platform profit is high AV cost under platform-owned AVs and low AV cost under individually owned AVs. Similarly, the structural effect of access to AVs on social welfare depends on who owns AVs. Access to individually owned AVs increases social welfare; in contrast, access to platform-owned AVs decreases social welfare—if and only if the AV cost is high. Managerial implications: Our results provide guidance to platforms, labor and consumer advocates, and governmental entities regarding regulatory and public policy decisions affecting the ease with which platforms obtain access to AVs.

scholarly journals Quantifying the Fleet Composition at Full Adoption of Shared Autonomous Electric Vehicles: An Agent-based Approach

2021 ◽  
Vol 15 (1) ◽  
pp. 47-60
Author(s):  
Peter Hogeveen ◽  
Maarten Steinbuch ◽  
Geert Verbong ◽  
Auke Hoekstra
Keyword(s):  
Electric Vehicles ◽  
Large Population ◽  
Environmental Benefits ◽  
Passenger Vehicle ◽  
Fleet Size ◽  
Agent Based ◽  
Passenger Vehicles ◽  
Vehicle Fleet ◽  
The Impact ◽  
Autonomous Electric Vehicles

Aims: Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Background: Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. Objective: To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. Methods: An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. Results: The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Conclusion: Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.

scholarly journals Allocation of COVID-19 Vaccines Under Limited Supply

2020 ◽  
Author(s):  
Xin Chen ◽  
Menglong Li ◽  
David Simchi-Levi ◽  
Tiancheng Zhao
Keyword(s):  
New York ◽  
Numerical Study ◽  
Age Groups ◽  
Problem Definition ◽  
Dynamic Allocation ◽  
Effective Interventions ◽  
Managerial Implications ◽  
Myopic Policy ◽  
The Government ◽  
Age Structured

Problem definition: This paper considers how to allocate COVID-19 vaccines to different age groups when limited vaccines are available over time. Academic/practical relevance: Vaccine is one of the most effective interventions to contain the ongoing COVID-19 pandemic. However, the initial supply of the COVID-19 vaccine will be limited. An urgent problem for the government is to determine who to get the first dose of the future COVID-19 vaccine. Methodology: We use epidemic data from New York City to calibrate an age-structured SAPHIRE model that captures the disease dynamics within and across various age groups. The model and data allow us to derive effective static and dynamic vaccine allocation policies minimizing the number of confirmed cases or the numbers of deaths. Results: The optimal static policies achieve a much smaller number of confirmed cases and deaths compared to other static benchmark policies including the pro rata policy. Dynamic allocation policies, including various versions of the myopic policy, significantly improve on static policies. Managerial implications: For static policies, our numerical study shows that prioritizing the older groups is beneficial to reduce deaths while prioritizing younger groups is beneficial to avert infections. For dynamic policies, the older groups should be vaccinated at early days and then switch to younger groups. Our analysis provides insights on how to allocate vaccines to the various age groups, which is tightly connected to the decision-maker's objective.

Children's Perceived Value: Conceptualization, Scale Development, and Validation

2020 ◽  
Author(s):  
Janine Williams ◽  
A Gazley ◽  
N Ashill
Keyword(s):  
New York ◽  
Perceived Value ◽  
Internal Consistency Reliability ◽  
Future Research ◽  
New York University ◽  
Consumer Decisions ◽  
Managerial Implications ◽  
Stage Process ◽  
Development And Validation ◽  
Value Measure

© 2020 New York University Perceived value among children is an important concept in consumer decisions, yet surprisingly no research has operationalized value for this consumer group. To address this omission, and following the guidelines of DeVellis (2016), this investigation reports the findings of a seven-stage process to develop a valid and reliable instrument for measuring perceived value among children aged 8–14 years. Value for children is conceptualized as a multidimensional construct capturing perceptions of what is received and what is given up, which differs from adult measures in terms of its composition and complexity. A 24-item scale is developed that shows internal consistency, reliability, construct validity, and nomological validity. We also demonstrate the validity of the new scale beyond an existing adult perceived value measure. Directions for future research and managerial implications of the new scale for studying children's consumer behavior are discussed.

Values of Voluntary Simplicity: Lifestyle and Motivation

1984 ◽  
Vol 55 (1) ◽  
pp. 231-240 ◽  
Author(s):  
Avraham Shama ◽  
Joseph Wisenblit
Keyword(s):  
United States ◽  
New York ◽  
New York City ◽  
York City ◽  
Metropolitan Areas ◽  
The United States ◽  
Voluntary Simplicity ◽  
Ecological Responsibility ◽  
Self Sufficiency ◽  
And Behavior

This paper describes the relation between values and behavior of a new life style, that of voluntary simplicity which is characterized by low consumption, self-sufficiency, and ecological responsibility. Also, specific hypotheses regarding the motivation for voluntary simplicity and adoption in two areas of the United States were tested. Analysis shows (a) values of voluntary simplicity and behaviors are consistent, (b) the motivation for voluntary simplicity includes personal preference and economic hardship, and (c) adoption of voluntary simplicity is different in the Denver and New York City metropolitan areas.

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